Multi-Objective Optimal Power Flow Solution Using a Modified Slime Mould Algorithm

Optimal power flow (OPF) analysis remains a fundamental tool for ensuring the efficient steady-state operation of AC interconnected power systems. While traditional numerical methods have long addressed OPF challenges, recent attention has shifted toward metaheuristic algorithms for their strength in handling high-dimensional, non-linear, and multimodal optimization. In this paper, we propose a (modified) multi-objective adaptation of the Slime Mould Algorithm (MO-SMA) to solve the OPF problem on the standard IEEE 30bus test system. The approach incorporates fitness ranking, repository updating, and refined crowding mechanisms to improve compromise solution density along the Pareto front. Experimental results show robust performance in cost-emission tradeoffs with acceptable convergence behavior and suggest further tuning of exploration-exploitation balance via control parameters and solution diversity enhancements.